Figuring Out the Fed—Beliefs about Policymakers and Gains from Transparency
用马尔可夫链蒙特卡洛算法估计了一个模型，其中私营部门对货币政策制定过程不确定，通过贝叶斯法则区分两种政策制定观点，研究关于美联储的信念演变及透明度的潜在收益。
In this paper, I use a Markov chain Monte Carlo algorithm to estimate a model of private‐sector behavior that does not feature private‐sector knowledge of the monetary policymaking process and, instead, leaves firms and households uncertain about how monetary policy is set. The private sector entertains two competing views of monetary policymaking, which I estimate. Firms and households use Bayes' law on a rolling data sample to distinguish between those two models. I use this setup to study the evolution of beliefs about the Federal Reserve and the possible gains from transparency.